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E. Becker and G. Schmitz

Abstract

A troposphere–stratosphere simple GCM that simulates the wintertime general circulation with considerable accuracy is presented. The model is driven by temperature relaxation, additional prescribed tropical heating, self-induced heating in midlatitudes, and boundary layer mixing. The idealizations in diabatic heating are used to study the basic impacts of orographic and midlatitude thermal forcing of stationary waves on the zonally averaged northern winter climatology in the troposphere.

It is found that large-scale mountains in the winter hemispheric midlatitudes do generally lead to enhanced eddy feedback onto the Hadley circulation; that is, the tropical streamfunction maximum is reduced and the surface near equatorward flow is enhanced due to enhanced eddy heat flux from the subtropics into midlatitudes. In addition, the subtropical jet is reduced and shifted poleward due to enhanced eddy deceleration in the poleward branch of the Hadley cell.

A prescribed longitude dependence of self-induced heating in the winter extratropics gives rise to quite an opposite response with regard to Hadley cell, subtropical Eliassen–Palm flux divergence, and eddy heat flux from the subtropics into midlatitudes. The subtropical jet is displaced equatorward and the overall wave activity shifts poleward. These effects depend on the nonlinear nature of self-induced midlatitude heating.

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A. Abdellaoui, F. Becker, and E. Olory-Hechinger

Abstract

In order to determine thermal inertia and latent heat flux from Meteosat data, we propose a model based on a Fourier analysis of the time variation of the surface temperature. This model uses as input the classical meteorological data (temperature, humidity and wind speed) measured in situ from meteorological stations and data obtained from Meteosat records (net radiation and surface temperature). The model is designed in such a way that the heat transfer resistances, which are very local quantities, are calculated by the model. The results of this model have been evaluated by comparison with experimental data and theoretical input data calculated from known in situ parameters. Both the accuracy and stability of these results, and the impact of errors of measurement on the input data will be discussed here. This model has been applied to the mapping of thermal inertia and evapotranspiration over a limited region of Mali within the Group Agro-Meteorological Project (GAMP). Results, on the whole, correspond to what is known of this region.

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J-M. Beckers, H. Burchard, E. Deleersnijder, and P. P. Mathieu

Abstract

A method to improve the behavior of the numerical discretization of a rotated diffusion operator such as, for example, the isopycnal diffusion parameterization used in large-scale ocean models based on the so-called z-coordinate system is presented. The authors then focus exclusively on the dynamically passive tracers and analyze some different approaches to the numerical discretization. Monotonic schemes are designed but are found to be rather complex, while simpler, linear schemes are shown to produce unphysical undershooting and overshooting. It is suggested that the choice of an appropriate discretization method depends on the importance of the rotated diffusion in a given simulation, whether the field to be diffused is dynamically active or not.

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R. W. Higgins, V. E. Kousky, V. B. S. Silva, E. Becker, and P. Xie

Abstract

A comparison of the statistics of daily precipitation over the conterminous United States is carried out using gridded station data and three generations of reanalysis products in use at the National Centers for Environmental Prediction (NCEP). The reanalysis products are the NCEP–NCAR reanalysis (Kalnay et al.), the NCEP–Department of Energy (DOE) reanalysis (Kanamitsu et al.), and the NCEP Climate Forecast System (CFS) reanalysis (Saha et al.). Several simple measures are used to characterize relationships between the observations and the reanalysis products, including bias, precipitation probability, variance, and correlation. Seasonality is accounted for by examining these measures for four nonoverlapping seasons, using daily data in each case. Relationships between daily precipitation and El Niño–Southern Oscillation (ENSO) phase are also considered.

It is shown that the CFS reanalysis represents a clear improvement over the earlier reanalysis products, though significant biases remain. Comparisons of the error patterns in the reanalysis products provide a suitable basis for confident conversion of the Climate Prediction Center (CPC) operational monitoring and prediction products to the new generation of analyses based on CFS.

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J. M. Beckers, H. Burchard, J. M. Campin, E. Deleersnijder, and P. P. Mathieu

Abstract

No abstract available.

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J. S. Becker, H. L. Taylor, B. J. Doody, K. C Wright, E. Gruntfest, and D. Webber

Abstract

A study was undertaken to review international literature pertaining to people’s behavior in and around floodwater. The review focused on people’s voluntary entry of floodwater. From the literature, five predominant reasons for entering floodwater were identified, including undertaking a recreational activity; attempting to reach a destination; retrieving property, livestock, or pets; undertaking employment duties; and rescuing or assisting with evacuation. Two primary influences on entering floodwater were found, namely risk perception (i.e., being unaware of or underestimating the risk from flooding) and social influences (i.e., being influenced by others). Demographics and environmental and temporal factors also played a part in decision-making about whether to enter floodwater or not. Emergency managers should take account of such factors when devising future public education strategies. Further research, including comparisons with current theoretical models, could help identify additional influences on decision-making for floodwater entry.

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T. H. M. Stein, W. Keat, R. I. Maidment, S. Landman, E. Becker, D. F. A. Boyd, A. Bodas-Salcedo, G. Pankiewicz, and S. Webster

Abstract

Since 2016, the South African Weather Service (SAWS) has been running convective-scale simulations to assist with forecast operations across southern Africa. These simulations are run with a tropical configuration of the Met Office Unified Model (UM), nested in the Met Office global model, but without data assimilation. For November 2016, convection-permitting simulations at 4.4- and 1.5-km grid lengths are compared against a simulation at 10-km grid length with convection parameterization (the current UM global atmosphere configuration) to identify the benefits of increasing model resolution for forecasting convection across southern Africa. The simulations are evaluated against satellite rainfall estimates, CloudSat vertical cloud profiles, and SAWS radar data. In line with previous studies using the UM, on a monthly time scale, the diurnal cycle of convection and the distribution of rainfall rates compare better against observations when convection-permitting model configurations are used. The SAWS radar network provides a three-dimensional composite of radar reflectivity for northeast South Africa at 6-min intervals, allowing the evaluation of the vertical development of precipitating clouds and of the timing of the onset of deep convection. Analysis of four case study days indicates that the 4.4-km simulations have a later onset of convection than the 1.5-km simulations, but there is no consistent bias of the simulations against the radar observations across the case studies.

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Michelle L. L’Heureux, Ken Takahashi, Andrew B. Watkins, Anthony G. Barnston, Emily J. Becker, Tom E. Di Liberto, Felicity Gamble, Jon Gottschalck, Michael S. Halpert, Boyin Huang, Kobi Mosquera-Vásquez, and Andrew T. Wittenberg

Abstract

The El Niño of 2015/16 was among the strongest El Niño events observed since 1950 and took place almost two decades after the previous major event in 1997/98. Here, perspectives of the event are shared by scientists from three national meteorological or climate services that issue regular operational updates on the status and prediction of El Niño–Southern Oscillation (ENSO). Public advisories on the unfolding El Niño were issued in the first half of 2015. This was followed by significant growth in sea surface temperature (SST) anomalies, a peak during November 2015–January 2016, subsequent decay, and its demise during May 2016. The life cycle and magnitude of the 2015/16 El Niño was well predicted by most models used by national meteorological services, in contrast to the generally overexuberant model predictions made the previous year. The evolution of multiple atmospheric and oceanic measures demonstrates the rich complexity of ENSO, as a coupled ocean–atmosphere phenomenon with pronounced global impacts. While some aspects of the 2015/16 El Niño rivaled the events of 1982/83 and 1997/98, we show that it also differed in unique and important ways, with implications for the study and evaluation of past and future ENSO events. Unlike previous major El Niños, remarkably above-average SST anomalies occurred in the western and central equatorial Pacific but were milder near the coast of South America. While operational ENSO systems have progressed markedly over the past several decades, the 2015/16 El Niño highlights several challenges that will continue to test both the research and operational forecast communities.

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Michelle L. L’Heureux, Michael K. Tippett, Ken Takahashi, Anthony G. Barnston, Emily J. Becker, Gerald D. Bell, Tom E. Di Liberto, Jon Gottschalck, Michael S. Halpert, Zeng-Zhen Hu, Nathaniel C. Johnson, Yan Xue, and Wanqiu Wang

Abstract

Three strategies for creating probabilistic forecast outlooks for El Niño–Southern Oscillation (ENSO) are compared. One is subjective and is currently used by the NOAA/Climate Prediction Center (CPC) to produce official ENSO outlooks. A second is purely objective and is based on the North American Multimodel Ensemble (NMME). A new third strategy is proposed in which the forecaster only provides the expected value of the Niño-3.4 index, and then categorical probabilities are objectively determined based on past skill. The new strategy results in more confident probabilities compared to the subjective approach and higher verification scores, while avoiding the significant forecast busts that sometimes afflict the NMME-based objective approach. The higher verification scores of the new strategy appear to result from the added value that forecasters provide in predicting the mean, combined with more reliable representations of uncertainty, which is difficult to represent because forecasters often assume less confidence than is justified. Moreover, the new approach can produce higher-resolution probabilistic forecasts that include ENSO strength information and that are difficult, if not impossible, for forecasters to produce. To illustrate, a nine-category ENSO outlook based on the new strategy is assessed and found to be skillful. The new approach can be applied to other outlooks where users desire higher-resolution probabilistic forecasts, including the extremes.

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Annarita Mariotti, Cory Baggett, Elizabeth A. Barnes, Emily Becker, Amy Butler, Dan C. Collins, Paul A. Dirmeyer, Laura Ferranti, Nathaniel C. Johnson, Jeanine Jones, Ben P. Kirtman, Andrea L. Lang, Andrea Molod, Matthew Newman, Andrew W. Robertson, Siegfried Schubert, Duane E. Waliser, and John Albers

Abstract

There is high demand and a growing expectation for predictions of environmental conditions that go beyond 0–14-day weather forecasts with outlooks extending to one or more seasons and beyond. This is driven by the needs of the energy, water management, and agriculture sectors, to name a few. There is an increasing realization that, unlike weather forecasts, prediction skill on longer time scales can leverage specific climate phenomena or conditions for a predictable signal above the weather noise. Currently, it is understood that these conditions are intermittent in time and have spatially heterogeneous impacts on skill, hence providing strategic windows of opportunity for skillful forecasts. Research points to such windows of opportunity, including El Niño or La Niña events, active periods of the Madden–Julian oscillation, disruptions of the stratospheric polar vortex, when certain large-scale atmospheric regimes are in place, or when persistent anomalies occur in the ocean or land surface. Gains could be obtained by increasingly developing prediction tools and metrics that strategically target these specific windows of opportunity. Across the globe, reevaluating forecasts in this manner could find value in forecasts previously discarded as not skillful. Users’ expectations for prediction skill could be more adequately met, as they are better aware of when and where to expect skill and if the prediction is actionable. Given that there is still untapped potential, in terms of process understanding and prediction methodologies, it is safe to expect that in the future forecast opportunities will expand. Process research and the development of innovative methodologies will aid such progress.

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